الصفحة 36
الصفحة 36
Designers' guide to EN 1997-1 Eurocode 7 : Geotechnical Design – General Rules
Designers' Guide to EN 1997-1 presents a detailed guide to the new Geotechnical Design Eurocode.As such it gives an invaluable insight into a code that, for the first time, provides a comprehensive design philosophy that is not only applicable to all forms of geotechnical problems but also shares a common philosophy with the design methodology for structures of all the commonly encountered construction materials.
Design Patterns in Modern C++20 : Reusable Approaches for Object-Oriented Software Design
As well as covering traditional design patterns, this book fleshes out new design patterns and approaches that will be useful to modern C++ developers. Author Dmitri Nesteruk presents concepts as a fun investigation of how problems can be solved in different ways, along the way using varying degrees of technical sophistication and explaining different sorts of trade-offs. You will: Use creational patterns such as builder, factories, prototype and singleton / Implement structural patterns such as adapter, bridge, decorator, facade and more / Work with the behavioral patterns such as chain of responsibility, command, iterator, mediator and more / Apply functional design patterns such as the Maybe Monad
Design of adaptive finite Element software : The finite element toolbox ALBERTA
During the last years, scientific computing has become an important research branch located between applied mathematics and applied sciences and engineering. Highly efficient numerical methods are based on adaptive methods, higher order discretizations, fast linear and non-linear iterative solvers, multi-level algorithms, etc. Such methods are integrated in the adaptive finite element software ALBERTA. It is a toolbox for the fast and flexible implementation of efficient software for real life applications, based on modern algorithms. ALBERTA also serves as an environment for improving existent, or developing new numerical methods in an interplay with mathematical analysis and it allows the direct integration of such new or improved methods in existing simulation software.
Design and Analysis of Thermal Systems
Bridges the gap between the theories of thermal science and design of practical thermal systems. Further, it discusses thermodynamic design principles, mathematical and CFD tools that will enable students as well as professional engineers to quickly analyze and design practical thermal systems. The major emphasis is on practical problems related to contemporary energy- and environment-related thermal systems including discussions on computational fluid dynamics used in thermal system design.
Design and analysis of randomized algorithms : Introduction to design paradigms
Randomness is a powerful phenomenon that can be harnessed to solve various problems in all areas of computer science. Randomized algorithms are often more efficient, simpler and, surprisingly, also more reliable than their deterministic counterparts. Computing tasks exist that require billions of years of computer work when solved using the fastest known deterministic algorithms, but they can be solved using randomized algorithms in a few minutes with negligible error probabilities. Introducing the fascinating world of randomness, this book systematically teaches the main algorithm design paradigms – foiling an adversary, abundance of witnesses, fingerprinting, amplification, and random sampling, etc. – while also providing a deep insight into the nature of success in randomization. Taking sufficient time to present motivations and to develop the reader's intuition, while being rigorous throughout, this text is a very effective and efficient introduction to this exciting field.
Design and Analysis of Learning Classifier Systems : A Probabilistic Approach
This book provides a comprehensive introduction to the design and analysis of Learning Classifier Systems (LCS) from the perspective of machine learning. LCS are a family of methods for handling unsupervised learning, supervised learning and sequential decision tasks by decomposing larger problem spaces into easy-to-handle subproblems.
Dependence in Probability and Statistics
This book gives a detailed account of some recent developments in the field of probability and statistics for dependent data. The book covers a wide range of topics from Markov chain theory and weak dependence with an emphasis on some recent developments on dynamical systems, to strong dependence in times series and random fields. A special section is devoted to statistical estimation problems and specific applications. The book is written as a succession of papers by some specialists of the field, alternating general surveys, mostly at a level accessible to graduate students in probability and statistics, and more general research papers mainly suitable to researchers in the field. The first part of the book considers some recent developments on weak dependent time series, including some new results for Markov chains as well as some developments on new notions of weak dependence. This part also intends to fill a gap between the probability and statistical literature and the dynamical system literature. The second part presents some new results on strong dependence with a special emphasis on non-linear processes and random fields currently encountered in applications. Finally, in the last part, some general estimation problems are investigated, ranging from rate of convergence of maximum likelihood estimators to efficient estimation in parametric or non-parametric time series models, with an emphasis on applications with non-stationary data.
Dentist on the Ward 2020 : An Introduction to Oral and Maxillofacial Surgery and Medicine For Core Trainees in Dentistry
Provides a concise introduction to the speciality and most of the conditions managed by Oral & Maxillofacial Surgeons in the UK. This includes the commonest Oral Medicine problems. It will be useful to those preparing for undergraduate and non-specialist post-graduate dental examinations.
Dental management of sleep disorders ; 2nd ed.
A clinically focused, updated, and expanded edition of the leading resource on the dental management of sleep disorders. Ddelivers a focused and authoritative exploration of the dentist’s role in managing patients with sleep problems, especially sleep-related breathing disorders and bruxism. Includes a variety of revealing case studies that examine the treatment of different sleep disorders, as well as: Thorough introductions to the societal impact of sleep disorders and human sleep architecture and functional anatomy of the airway Comprehensive explorations of the pathophysiology and classification of sleep disorders and sleep disorders in the pediatric population Practical discussions of medical disorders related to obstructive sleep apnea and the dental and orofacial consequences of sleep-related breathing disorders In-depth examinations of the role and interaction of the dentist with the sleep physician and sleep study center
Deep Learning-Based Face Analytics
Provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field.
Deep Learning to See : Towards New Foundations of Computer Vision
Topics and features: Presents a curiosity-driven approach, posing questions to stimulate readers to design novel computational models of vision Offers a rethinking of computer vision, arguing for an approach based on vision in nature, versus regarding visual signals as collections of images Provides an interdisciplinary commentary, aiming to unify computer vision, machine learning, human vision, and computational neuroscience Serving to inspire and stimulate critical reflection and discussion, yet requiring no prior advanced technical knowledge, the text can naturally be paired with classic textbooks on computer vision to better frame the current state of the art, open problems, and novel potential solutions.
Deep learning pipeline : Building a deep learning model with TensorFlow
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets.
Deep learning for computational problems in hardware security : Modeling attacks on strong physically unclonable function circuits
Discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promising hardware security primitives. The volume is self-contained and includes a comprehensive background on PUF circuits, and the necessary mathematical foundation of traditional and advanced machine learning techniques such as support vector machines, logistic regression, neural networks, and deep learning. This book can be used as a self-learning resource for researchers and practitioners of hardware security, and will also be suitable for graduate-level courses on hardware security and application of machine learning in hardware security.
Deep learning and computer vision in remote sensing-II
Computer vision (CV) have seen a massive rise in popularity in the remote sensing field over the last few years. This success is mostly due to the effectiveness of deep learning (DL) algorithms. However, remote sensing data acquisition and annotation, as well as information extraction from massive remote sensing data, are still challenging. This reprint collected novel developments in the field of deep learning and computer vision methods for remote sensing. Papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems, have been published. With practical examples and real-world case studies, this reprint provides a valuable resource for researchers, professionals, and students seeking to harness the power of deep learning in the field of remote sensing.
Deep learning and computer vision in remote sensing-I
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
Deep fake detection
Deep learning has been successfully applied to solve various complex problems ranging from big data analytics to computer vision and human-level control. Deep learning advances however have also been employed to create software that can cause threats to privacy, democracy and national security. One of those deep learning-powered applications recently emerged is “deepfake”. Deepfake algorithms can create fake images and videos that humans cannot distinguish them from authentic ones. The proposal of technologies that can automatically detect and assess the integrity of digital visual media is therefore indispensable.
Declarative agent languages and technologies II ; 2nd international workshop, DALT 2004, New York, NY, USA, July 19, 2004, revised selected papers
Nearly 40 research groups worldwide were motivated to contribute to this event by submitting their most recent research achievements, covering a wide variety of the topics listed in the call for papers. More than 30 top researchers agreed to join the Program Committee, which then collectively faced the hard task of selecting the one-day event program. The fact that research in multi-agent systems is no longer only a novel and promising research horizon at dawn is, in our opinion, the main reason behind DALT’s (still short) success story. On the one hand, agent theories and app- cations are mature enough to model complex domains and scenarios, and to successfully address a wide range of multifaceted problems, thus creating the urge to make the best use of this expressive and versatile paradigm, and also pro?t from all the important results achieved so far. On the other hand, bui- ing multi-agent systems still calls for models and technologies that could ensure system predictability, accommodate ?exibility, heterogeneity and openness, and enable system veri?cation.
Decision Support for Global Enterprises
Decision Support for Global Enterprises consists of peer-reviewed and invited papers with two primary goals: (1) Stimulate creative discussion between academic researchers and the practitioner IS community to improve the research and practice in the area. (2) Increase awareness of the problems and challenges faced by global enterprises that can be met with innovative decision support systems. Limitations are also explored, covering the following topics: the emerging enterprise decision making processes and technologies; decision making in uncertain, changing conditions; the changing infrastructure in organizations and society; the expanding role of web technologies; and emerging theories and practices for managing knowledge and making decisions.
Decision Support for Forest Management
While earlier books concerning forest planning have tended to focus on linear programming, economic aspects, or specific multi-criteria decision aid tools, this book provides a much broader range of tools to meet a variety of planning situations. The methods themselves cover a range of decision situations – from cases involving single decision makers, through group decision making, to participatory planning. They include traditional decision support tools, from optimization to utility functions, as well as methods that are just gaining ground in forest planning – such as problem structuring methods and social choice theory. Including examples which illustrate the application of each technique to specific management planning problems, the book offers an invaluable resource for both researchers and advanced students specializing in management and planning issues relating to forestry.
Decision Making for Complex Socio-Technical Systems : Robustness from Lessons Learned in Long-Term Radioactive Waste Governance
The long-term governance of radioactive waste continues to be a major complex and contentious socio-technical issue worldwide. Traditionally, it has been considered as mainly a challenge to scientists and engineers to develop technical "solutions" to specific problems. But increasingly these narrow solutions have been enlarged by wider societal considerations such as ethics, public involvement, control and retrievability – needs that have in the meanwhile been recognised by the nuclear community, at least in a general way. In this book, we analyse motives for a broad discourse as well as suggest prerequisites to launch it. The author attempts to give a novel, empirically based and technically sound treatment of fundamental issues in long-term management and governance. Written to be accessible to a wide selection of the interested public, the study proposes a combination of technical design issues, analysis methods and institutional backup in a dynamic procedure, and with involvement at all levels of political, commercial and social life.
